Modeling of Online Learning Strategies Based on Fuzzy Expert Systems and Self-Directed Learning Readiness: The Effect on Learning Outcomes

This study proposes an online learning model based on fuzzy expert systems to recommend learning contents that are most appropriate for facilitating more efficient learning. The process used two computer applications which are Matlab for fuzzy analysis and the learning management system Moodle platform for online learning environment. Besides, considering the learner themselves by their self-directed learning readiness as the moderating variable in this study. To examine the learning strategies, we used aptitude treatment interaction for the learning model. Statistical analysis is used to examine the effect of this strategy and the students' self-directed learning readiness on the learning outcomes. We found that students who are taught by online learning strategies based on fuzzy expert systems have better learning outcomes than students who are given traditional online learning strategies. Students who have high self-directed learning readiness have higher learning outcomes than students who have low self-directed learning readiness in both online learning strategies. Students who have low self-directed learning readiness are more appropriate to learn by the online learning strategies based on fuzzy expert systems to improve their learning outcomes